Robot Arm Trajectory Tracking based on adaptive neural Control

2019 International Conference on Advanced Electronic Materials, Computers and Materials Engineering

无线电电子学;计算机科学;材料科学

Long, Luo^1

Mechanical and Electrical Department, Guangzhou Institute of Technology, Guangzhou,Guangdong

510075, China^1

关键词: Adaptive neural control;    Adaptive neural network control;    Desired trajectories;    Dynamic uncertainty;    Neural network approximation;    Nonlinear uncertain systems;    Robot arm trajectories;    Trajectory tracking;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/563/5/052066/pdf
DOI  :  10.1088/1757-899X/563/5/052066

来源: IOP

【 摘 要 】

Control system of robot arm is a multi-variable, strong coupling, and highly nonlinear uncertain system, and trajectory tracking requires the robot manipulator to move according to a desired trajectory that has been given. According to friction and disturbance problem, an adaptive neural network control is proposed. Neural network is used to compensate the dynamic uncertainty of system, and the neural network approximation error and friction and disturbance part are compensated by an parameter adaptive compensation. The simulation results show that this algorithm can improve the effectiveness and accuracy of mechanical arm trajectory tracking.